Intelligence analysis of Tay Twitter bot

The aim of this paper is to provide a framework to understand and analyse the intelligence of chat-bots. With the ever increasing number of chat-bots available, we have considered intelligence analysis to be a functional parameter to determine the usefulness of a bot. For our analysis, we consider Microsoft's Twitter bot Tay released for online interaction in March 2016. We perform various natural language processing tasks on the tweets tweeted by and tweeted at Tay and discuss the implications of the results. We perform classification, text categorization, entity extraction, latent Dirichlet allocation analysis, frequency analysis and model the vocabulary used by the bot using a word2vec system to achieve this goal. Using the results from our analysis we define a metric called the bot intelligence score to evaluate and compare the intelligence of bots in general.